The transmission of various types of digital data between computers continues to grow in importance. The predominant method of transmitting such digital data includes coding the digital data into a low frequency base data signal and modulating the base data signal onto a high frequency carrier signal. The high frequency carrier signal is then transmitted across a network cable medium, via RF signal, modulated illumination, or other network medium, to a remote computing station.
At the remote computing station, the high frequency carrier signal must be received and demodulated to recover the original base data signal. In the absence of any distortion of the carrier signal across the network medium, the received carrier would be identical in phase, amplitude, and frequency to the transmitted carrier and could be demodulated using known mixing techniques to recover the base data signal. The base data signal could then be recovered into digital data using known sampling algorithms.
However, the network topology tends to distort the high frequency carrier signal due to numerous branch connections and different lengths of such branches causing numerous reflections of the transmitted carrier. Such problems are even more apparent in a network which uses home telephone wiring cables as the network cable medium because the numerous branches and connections are typically designed for transmission of plain old telephone system POTS signals in the 0.3-3.4 kilohertz frequency range and are not designed for transmission of high frequency carrier signals on the order of 7 Megahertz.
A typical approach for recovering transmitted data at a receiver operating in such an environment includes the use of an adaptive equalizer for filtering noise and distortion on the received carrier signal. In theory, an equalized signal should match the signal originally transmitted such that a slicer can accurately map the signal to defined constellation points to recover the originally transmitted data.
Known equalizers comprise a complex finite impulse response (FIR) filter comprising an arrangement of four multi-tap FIR filters, each utilizing upward of 11 coefficients. Therefore, the entire complex FIR filter arrangement can use on the order of 44 coefficients. Typically, each of these coefficients is an 11-bit coefficient to maintain an adequate signal to noise ratio. The value of each coefficient is calculated during the training sequence of a frame such that the coefficients are “custom” calculated for the particular distortion present during the short duration of time in which the frame is transmitted and received. A problem associated with such receivers is that coefficient calculation circuitry needed for calculating upward of 44 11-bit coefficients within the short duration of the training period of a frame can require upward of 2.7 billion operations per second. This requires high-speed and costly digital signal processing circuits. Such circuits consume substantial amount of power and are relatively expensive. As a result, such circuits are not practical in battery powered devices for power consumption reasons, and are unsuitable for inexpensive consumer network devices such as smoke detectors, door openers and other devices requiring inexpensive network access.
Therefore, based on recognized industry goals for size, cost, and power reductions, what is needed is a device and method for determining coefficient values that does not suffer the disadvantages of known systems.